Antiplatelet Therapy in Patients with Unstable Angina and Non–ST‐Segment‐Elevation Myocardial Infarction: Findings from the CRUSADE National Quality Improvement Initiative
Bibliographic record
Abstract
Evidence-based clinical practice guidelines encapsulate current knowledge to guide health care professionals in the treatment of patients with unstable angina or non-ST-segment-elevation myocardial infarction (NSTEMI), yet adherence to guideline recommendations is suboptimal. Guideline adherence may be improved by quality improvement programs such as the CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation?) National Quality Improvement Initiative of the American College of Cardiology-American Heart Association Guidelines. The CRUSADE data have been analyzed to demonstrate that overall guideline adherence is directly associated with mortality and that improvement in guideline adherence saves lives. Also, the CRUSADE data have determined that the real-life mortality risk associated with unstable angina and NSTEMI is greater than suggested by clinical trials. The newer antiplatelet drugs recommended in early intervention and discharge treatment strategies are underused across many segments of the unstable angina-NSTEMI population. Glycoprotein IIb-IIIa inhibitors are underused in high-risk populations, and clopidogrel is markedly underused in patients who are medically managed rather than undergoing percutaneous coronary intervention or coronary artery bypass graft surgery. In addition, often the specialty of the treating physician and the status of the hospital influence the use of antiplatelet therapy. The reasons for underprescribing of antiplatelet drugs by physicians are not entirely clear but may be related to a lack of guideline familiarity and understanding, as well as factors such as drug novelty, safety, and cost. Continued education and data dissemination are therefore vital in promoting the prescription of guideline-recommended drugs, both in the early hospitalization phase and as patients transition to community-based care. The role of the pharmacist is pivotal in ensuring adherence to clinical guidelines by interacting with both the physician and patient.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".